Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

5 papers of 6,984Sort Recent · Most cited
  1. 2025
    SDP: Spectral-Decomposed Prompting for Continual LearningSiqi Song, Limin Yu, Jimin XiaoACM International Conference on Multimedia · Xi’an Jiaotong-Liverpool University
  2. 2025
    You look from old classes: Towards accurate few shot class-incremental learningYijie Hu, Kaizhu Huang, Wei Wang … Qiufeng WangPattern Recognition · University of Liverpool · Xi’an Jiaotong-Liverpool University · +1
  3. 2025
    TIPS: Two-level prompt selection for more stability-plasticity balance in continual learningZhikun Feng, Liang Peng, Kang Dang … Jionglong SuPattern Recognition · University of Electronic Science and Technology of China · Chengdu University of Information Technology · +3
  4. 2025
    Decoupling Overlapped Feature Spaces: When Continual Learning Meets Fine-Grain ClassificationZhikun Feng, Mingyu Wu, Ping Kuang … Yu LiuIEEE International Conference on Multimedia and Expo (ICME) · University of Electronic Science and Technology of China · Xi’an Jiaotong-Liverpool University
  5. 2025
    Covariance-Based Space Regularization for Few-Shot Class Incremental LearningYijie Hu, Guanyu Yang, Zhaorui Tan … Qiufeng WangWACV · Xi’an Jiaotong-Liverpool University · University of Liverpool · +1
    PDF ↗
About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.